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[论文解读] Avalanche analysis from multi-electrode ensemble recordings in cat, monkey and human cerebral cortex during wakefulness and sleep

Nima Dehghani, Nicholas G. Hatsopoulos|arXiv (Cornell University)|Mar 4, 2012
Neural dynamics and brain function参考文献 15被引用 9
一句话总结

本研究利用高密度多电极记录技术,在猫、猴和人类清醒与睡眠状态下的哺乳动物大脑皮层中,研究了自组织临界性。尽管先前报告称神经元级联呈现幂律缩放,但严格的统计分析显示,在单个神经元活动或局部场电位(LFP)峰值中均无确凿证据表明存在幂律分布;相反,双指数分布提供了最佳拟合,表明大脑动力学更宜用多种指数过程而非临界性来描述。

ABSTRACT

Self-organized critical states are found in many natural systems, from earthquakes to forest fires, they have also been observed in neural systems, particularly, in neuronal cultures. However, the presence of critical states in the awake brain remains controversial. Here, we compared avalanche analyses performed on different in vivo preparations during wakefulness, slow-wave sleep and REM sleep, using high-density electrode arrays in cat motor cortex (96 electrodes), monkey motor cortex and premotor cortex and human temporal cortex (96 electrodes) in epileptic patients. In neuronal avalanches defined from units (up to 160 single units), the size of avalanches never clearly scaled as power-law, but rather scaled exponentially or displayed intermediate scaling. We also analyzed the dynamics of local field potentials (LFPs) and in particular LFP negative peaks (nLFPs) among the different electrodes (up to 96 sites in temporal cortex or up to 128 sites in adjacent motor and pre-motor cortices). In this case, the avalanches defined from nLFPs displayed power-law scaling in double log representations, as reported previously in monkey. However, avalanche defined as positive LFP (pLFP) peaks, which are less directly related to neuronal firing, also displayed apparent power-law scaling. Closer examination of this scaling using more reliable cumulative distribution functions (CDF) and other rigorous statistical measures, did not confirm power-law scaling. The same pattern was seen for cats, monkey and human, as well as for different brain states of wakefulness and sleep. We also tested other alternative distributions. Multiple exponential fitting yielded optimal fits of the avalanche dynamics with bi-exponential distributions. Collectively, these results show no clear evidence for power-law scaling or self-organized critical states in the awake and sleeping brain of mammals, from cat to man.

研究动机与目标

  • 检验自组织临界性(SOC)是否在清醒和睡眠的哺乳动物皮层动力学中起作用。
  • 解决跨物种和脑状态的在体准备中神经元级联缩放的矛盾报告。
  • 评估LFP中看似幂律缩放是否为阈值设定或容积导体效应的产物,而非真正的临界动力学。
  • 应用严格的统计方法,区分神经元级联数据中真实幂律缩放与替代分布。

提出的方法

  • 使用高密度多电极阵列(96–128个电极)记录猫运动皮层、猴运动/前运动皮层以及人类颞叶皮层的单个神经元活动和局部场电位(LFP)。
  • 从动作电位爆发和LFP峰值(包括负向和正向)定义神经元级联,大小以参与的电极或单位数量衡量。
  • 统计分析采用累积分布函数(CDF)、Kolmogorov-Smirnov检验以及带置信区间的幂律拟合,以严格检验尺度不变性。
  • 对替代分布(尤其是双指数模型)进行拟合并使用似然比检验和拟合优度指标进行比较。
  • 在多个脑状态(清醒、慢波睡眠、快速眼动睡眠)和物种间重复分析,以评估一致性。
  • 对容积导体效应进行建模,以检验LFP信号的空间扩散是否可能人为放大大型级联的尺寸。

实验结果

研究问题

  • RQ1在清醒和睡眠的哺乳动物皮层中,神经元级联是否表现出自组织临界性所预期的真实幂律缩放?
  • RQ2LFP峰值中看似幂律分布是否为阈值设定或容积导体效应所致,而非真正的临界动力学?
  • RQ3在不同物种和脑状态中,单个神经元活动的缩放特性与LFP的缩放特性相比如何?
  • RQ4与幂律分布相比,指数或双指数等替代分布是否对级联大小分布提供更优的统计拟合?
  • RQ5所观察到的动力学是否可由反映潜在兴奋-抑制平衡的多种指数过程来解释?

主要发现

  • 在猫、猴或人类的单个神经元活动衍生的级联大小分布中,无论处于何种脑状态,均未发现显著的幂律缩放。
  • 基于负向LFP峰值(nLFPs)的LFP级联在双对数图中显示看似幂律缩放,但严格的CDF和Kolmogorov-Smirnov检验否定了其为真实幂律。
  • 与动作电位关联较弱的正向LFP峰值(pLFPs)也表现出看似幂律缩放,但同样被统计检验所否定。
  • 双指数分布对所有物种和条件下的级联大小数据提供了最佳拟合,表明双重指数过程可能主导皮层动力学。
  • 统计检验证实,有界拟合程序可能使结果偏向幂律拟合,且此类拟合在缺乏严格验证时不可靠。
  • 容积导体效应可能人为放大LFP记录中的大型级联尺寸,提示在解释空间扩展时应谨慎,避免将其误认为真实的网络级联。

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